AI Engineer

We're looking for an AI Engineer to contribute to the development and delivery of AI/ML systems. This role is ideal for an early-career engineer who is comfortable writing code, eager to take on real responsibility, and ready to grow their craft. 

In this role, you will work as a contributing member of a cross-functional team, building and supporting AI/ML models, pipelines, and the systems around them. You'll take ownership of well-scoped tasks, learn from more senior engineers, and steadily expand the surface area you can confidently deliver on. You'll be joining real, in-flight work where reliability and quality matter. You'll collaborate closely with experienced engineers to build new capabilities, improve existing systems, and develop the technical instincts that come from shipping things that matter. 

Why This Role Matters 

At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate. 
 
Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on. 

What You’ll Do 

Craft & Delivery 

• Build and ship features of AI/ML and LLM-powered systems with guidance from senior engineers, contributing to solutions that run in production 

• Implement and maintain components of AI/ML and AI agent pipelines from data ingestion through model deployment, picking up the unglamorous parts as you grow 

• Contribute to LLM-powered features such as prompts, evaluations, retrieval, and tool integrations, working alongside senior engineers 

• Handle data preprocessing, feature engineering, and basic evaluation to prepare quality inputs and validate model and prompt performance 

Collaboration & Communication 

• Work closely with engineers across a distributed, cross-functional team to move projects forward effectively 

• Document experiments, results, and model decisions clearly so findings can be built upon, replicated, and shared across the team 

• Participate in code reviews and team discussions, contributing your perspective and incorporating feedback 

Leadership & Influence 

• Take ownership of assigned tasks and deliver end-to-end with consistency and follow-through 

• Share learnings from experiments and research with the broader team, contributing to a culture of continuous improvement 

• Bring intellectual curiosity to every problem — ask good questions, explore new approaches, and stay hungry to grow your craft 

What You’ll Bring 

• 3+ years of professional software engineering experience, with hands-on exposure to AI/ML systems and generative AI development 

• Solid software engineering foundation (Python or similar) 

• Foundational knowledge of cloud platforms (AWS, GCP, or Azure), with interest in deepening AWS and AWS GenAI expertise 

• Exposure to building or contributing to agentic AI systems alongside more senior engineers 

• Familiarity with AI frameworks and orchestration tools 

• Familiarity with evaluation and observability practices for LLM apps 

• Awareness of AI safety, responsible AI principles, prompt injection risks, and PII handling 

• Exposure to RAG pipelines: chunking strategies, embedding models, and vector databases 

• Experience building or integrating with APIs, including internal and third-party services 

• Awareness of LLM cost considerations such as token economics and caching strategies 

• Working knowledge of Docker for containerized deployments, with exposure to Kubernetes 

• Demonstrable, day-to-day usage of AI-forward coding tools such as Claude Code and Cursor 

Helpful Extras and Unique Skills 

You’ll Do Well Here if You Are 

• A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty. 

• A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway. 

• Direct in a way that makes the work better.